Wear Patterns: How What’s Missing Can Help Us See Data Better

A little girl said her favorite color was pink. Her dad said he could prove her wrong. He took all her colored pencils and lined them up by length. The result was obvious: her most-used colored pencil was blue, not pink. It’s hard to argue with the data.

This got me thinking. What other kinds of answers can we find by looking at data that appears in the real world as a byproduct of what has been “used up” or “worn down”? What can we tell from what’s left over?

Quite a lot, it turns out. Rebecca Saltzman, a director of the Bay Area Rapid Transit, recently shared an image of rail spikes pulled from the BART tracks. Compared to the new one in the center, the old, rusted spikes look dangerously worn away. This display of visual evidence – an inadvertent bar chart – makes one thing extremely clear: BART is in dire need of repair.

If you’ve ever ventured out of the house in the few hours or days after a huge snow storm, you’ve likely noticed something different about street corners. Namely, that they are covered in inches of snow. Despite snow plows’ best efforts, these mountains of snow build up over days and can stick out many feet from the curb. And this leftover snow can actually reveal valuable information: the places where cars don’t drive.

Once again, the visual evidence of what’s been used (or in this case, driven over) is valuable data. Leftover snow could provide urban designers, transportation engineers and pedestrian activists with important data to make real world public safety decisions. It could also inspire more creative and less costly ways to build better and safer streets.

Wear patterns have long provided important indicators to help keep us safe. For example, checking out the wear pattern of your car tire’s tread can help you determine whether your tires are over-inflated, out of balance or misaligned. A garage in upstate New York published a visual guide to the ways the tread on your car tires can wear, and what each pattern may mean:

Runners are often told to inspect the soles of their running shoes to gather clues about how they run. For example, if your right shoe is markedly more worn down than your left, your quirky running form may be setting you up for more injuries. But even symmetrical wear patterns can be revealing. They can show whether you tend to land toe or heel-first, or how far your foot rolls inward (or “pronates”), when you hit the ground.

Coaches, trainers, and physical therapists alike have long drawn connections between certain wear patterns and getting injured (or not). Not surprisingly, so have shoe companies. Pronate too much? You need this motion-control shoe. Not enough? This cushioned shoe is for you. According to the advertisements, the data on the bottom of your shoe will help you find the perfect Cinderella fit.

Of course there are many other examples out there of data appearing as a real world byproduct of use or wear. Cases where what’s been used up, leftover, missing or accumulated can give us valuable insights or help us make better decisions about health and safety, design, or policy changes.

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